Performance and validation of a digital memory test across the Alzheimer's Disease continuum

Abstract Digital cognitive testing using online platforms has emerged as a potentially transformative tool in clinical neuroscience. In theory, it could provide a powerful means of screening for and tracking cognitive performance in people at risk of developing conditions such as Alzheimer’s Disease (AD). Here we investigate whether digital metrics derived from a tablet-based short-term memory task – “What was where?” Oxford Memory Task – were able to clinically stratify patients at different points within the AD continuum and to track disease progression over time. Performance of these metrics to traditional neuropsychological pen-and-paper screening tests of cognition was also analyzed. A total of 325 people participated in this study: 49 patients with subjective cognitive impairment (SCI), 57 with mild cognitive impairment (MCI), 63 with AD dementia and 156 elderly healthy controls (EHC). Most digital metrics were able to discriminate between healthy controls and patients with MCI and between MCI and AD patients. Some, including Absolute Localization Error, also differed significantly between patients with SCI and MCI. Identification accuracy was the best predictor of hippocampal atrophy, performing as well as standard screening neuropsychological tests. A linear support vector model combining digital metrics achieved high accuracy and performed at par with standard testing in discriminating between EHC and SCI (AUC 0.82) and between SCI and MCI (AUC 0.92). Memory imprecision was able to predict cognitive decline on standard cognitive tests over one year. Overall, these findings show how it might be possible to use a digital memory test in clinics and clinical trial contexts to stratify and track performance across the Alzheimer’s disease continuum.